Smart Firefighting: A Deep Learning Approach to Tracking Firefighter Movements
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10259280" target="_blank" >RIV/61989100:27240/25:10259280 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/25:10259280
Result on the web
<a href="https://ieeexplore.ieee.org/document/11268769" target="_blank" >https://ieeexplore.ieee.org/document/11268769</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICUMT67815.2025.11268769" target="_blank" >10.1109/ICUMT67815.2025.11268769</a>
Alternative languages
Result language
angličtina
Original language name
Smart Firefighting: A Deep Learning Approach to Tracking Firefighter Movements
Original language description
In recent years, there has been increased interest in using advanced technologies such as artificial intelligence, particularly in public safety and rescue operations. This paper focuses on an innovative approach to monitoring and analysing the movement of firefighters during rescue operations using artificial intelligence. In our research, we implemented a system that uses data obtained from sensors placed on the protective suits of firefighters. This data is analysed using deep-learning neural networks after advanced data preprocessing. The goal is to provide a more accurate real-time interpretation of firefighter movement, improving rescue teams’ coordination and increasing firefighters’ safety in their work. This paper presents the results of initial experiments that demonstrate the effectiveness of the proposed system in different rescue operation scenarios. At the end of the paper, we also discuss possible challenges and directions for further research in this area. Our work represents an important step towards integrating artificial intelligence into critical public safety operations. It offers new opportunities for improving rescue operations and protecting lives.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/VJ02010037" target="_blank" >VJ02010037: Monitoring the position of IRS members even during an intervention in large buildings using elements of artificial intelligence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
International Congress on Ultra Modern Telecommunications and Control Systems and Workshops 2025
ISBN
979-8-3315-7676-9
ISSN
2157-0221
e-ISSN
2157-023X
Number of pages
8
Pages from-to
"neuvedeno"
Publisher name
IEEE
Place of publication
Piscataway
Event location
Florencie
Event date
Nov 3, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001669273500041